Protein Engineering

gb1 · Fully connected

reference_gb1_fc_plm_modulof3_20261105-035924

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10tie_share_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50tie_share_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100tie_share_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pcttie_share_at_1pctcaptured_at_1pct
train0.30150.97820.97140.944229512.00000.82851966.00001.00001.31321.45260.00000.00000.91601.00001.23641.45260.24000.00000.95261.00001.18921.45260.37000.00000.95990.99900.89821.67260.66330.00000.9776
validation4.33070.25350.24970.06273230.0000-0.057918775.00000.4000-1.42070.72870.00000.00000.22350.3400-1.35750.74170.00000.00000.24930.3100-1.49960.74170.00000.00000.21530.2786-1.55671.21150.00500.00000.2048
test4.01440.31780.30510.08474705.00000.02772708.00000.80000.12811.61320.00000.00000.50810.72000.18901.61320.00000.00000.56120.71000.17711.61320.01000.00000.57200.68000.10331.61320.01500.00000.5691

Loss per epoch

training validation

Config

name: reference_gb1_fc_plm_modulof3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 3
model:
  name: fcn
  hidden:
  - 1000
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7